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We propose GaussCtrl, a text-driven method to edit a 3D scene reconstructed by the 3D Gaussian Splatting (3DGS).
Zwicker, M., Pfister, H., van Baar, J., Gross, M.: Ewa volume splatting. In: Proceedings Visualization, 2001. VIS ’01. pp. 29–538 (2001). https://doi.org/10.1109/VISUAL.2001.964490
2001
Earlier work this paper cites.
2010
Earlier work this paper cites.
Sohl-Dickstein, J., Weiss, E.A., Maheswaranathan, N., Ganguli, S.: Deep unsupervised learning using nonequilibrium thermodynamics. p. 2256–2265. ICML’15, JMLR.org (2015)
2015
Earlier work this paper cites.
Gatys, L.A., Ecker, A.S., Bethge, M.: Image style transfer using convolutional neural networks. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 2414–2423 (2016). https://doi.org/10.1109/CVPR.2016.265
2016
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2020
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Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis (2020)
2020
Earlier work this paper cites.
Yao, Y., Luo, Z., Li, S., Zhang, J., Ren, Y., Zhou, L., Fang, T., Quan, L.: Blendedmvs: A large-scale dataset for generalized multi-view stereo networks. Computer Vision and Pattern Recognition (CVPR) (2020)
2020
Earlier work this paper cites.
Dhariwal, P., Nichol, A.: Diffusion models beat gans on image synthesis. ArXiv abs/2105.05233
2021
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Gal, R., Patashnik, O., Maron, H., Chechik, G., Cohen-Or, D.: Stylegan-nada: Clip-guided domain adaptation of image generators (2021)
2021
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Nichol, A., Dhariwal, P.: Improved denoising diffusion probabilistic models. ArXiv abs/2102.09672
2021
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Barron, J.T., Mildenhall, B., Verbin, D., Srinivasan, P.P., Hedman, P.: Mip-nerf 360: Unbounded anti-aliased neural radiance fields. CVPR (2022)
2022
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Hertz, A., Mokady, R., Tenenbaum, J., Aberman, K., Pritch, Y., Cohen-Or, D.: Prompt-to-prompt image editing with cross attention control (2022)
2022
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Ho, J.: Classifier-free diffusion guidance. ArXiv abs/2207.12598
2022
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Hu, E.J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., Chen, W.: LoRA: Low-rank adaptation of large language models. In: International Conference on Learning Representations (2022), https://openreview.net/forum?id=nZeVKeeFYf9
2022
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Huang, Y.H., He, Y., Yuan, Y.J., Lai, Y.K., Gao, L.: Stylizednerf: Consistent 3d scene stylization as stylized nerf via 2d-3d mutual learning. In: Computer Vision and Pattern Recognition (CVPR) (2022)
2022
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Li, B., Weinberger, K.Q., Belongie, S., Koltun, V., Ranftl, R.: Language-driven semantic segmentation. In: International Conference on Learning Representations (2022), https://openreview.net/forum?id=RriDjddCLN
2022
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2022
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Li, F., Zhang, H., Liu, S., Guo, J., Ni, L.M., Zhang, L.: Dn-detr: Accelerate detr training by introducing query denoising. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 13619–13627 (2022)
2022
Cited alongside, same era.
Li*, L.H., Zhang*, P., Zhang*, H., Yang, J., Li, C., Zhong, Y., Wang, L., Yuan, L., Zhang, L., Hwang, J.N., Chang, K.W., Gao, J.: Grounded language-image pre-training. In: CVPR (2022)
2022
Cited alongside, same era.
Liu, S., Li, F., Zhang, H., Yang, X., Qi, X., Su, H., Zhu, J., Zhang, L.: DAB-DETR: Dynamic anchor boxes are better queries for DETR. In: International Conference on Learning Representations (2022), https://openreview.net/forum?id=oMI9PjOb9Jl
2022
Cited alongside, same era.
Luo, C.: Understanding diffusion models: A unified perspective. ArXiv abs/2208.11970
2022
Cited alongside, same era.
Epstein, D., Jabri, A., Poole, B., Efros, A.A., Holynski, A.: Diffusion self-guidance for controllable image generation (2023)
2023
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Haque, A., Tancik, M., Efros, A., Holynski, A., Kanazawa, A.: Instruct-nerf2nerf: Editing 3d scenes with instructions. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (2023)
2023
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Hertz, A., Aberman, K., Cohen-Or, D.: Delta denoising score (2023)
2023
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Kerbl, B., Kopanas, G., Leimkühler, T., Drettakis, G.: 3d gaussian splatting for real-time radiance field rendering. ACM Transactions on Graphics 42
2023
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2022
Cited alongside, same era.
von Platen, P., Patil, S., Lozhkov, A., Cuenca, P., Lambert, N., Rasul, K., Davaadorj, M., Wolf, T.: Diffusers: State-of-the-art diffusion models. https://github.com/huggingface/diffusers (2022)
2022
Cited alongside, same era.
2022
Cited alongside, same era.
2022
Cited alongside, same era.
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 10684–10695 (2022)
2022
Cited alongside, same era.
2022
Cited alongside, same era.
2022
Cited alongside, same era.
Zhang, H., Li, F., Liu, S., Zhang, L., Su, H., Zhu, J., Ni, L.M., Shum, H.Y.: Dino: Detr with improved denoising anchor boxes for end-to-end object detection (2022)
2022
Cited alongside, same era.
2023
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Liu, K., Zhan, F., Chen, Y., Zhang, J., Yu, Y., Saddik, A.E., Lu, S., Xing, E.: Stylerf: Zero-shot 3d style transfer of neural radiance fields (2023)
2023
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2023
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2023
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2023
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2023
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Pan, X., Tewari, A., Leimkühler, T., Liu, L., Meka, A., Theobalt, C.: Drag your gan: Interactive point-based manipulation on the generative image manifold. In: ACM SIGGRAPH 2023 Conference Proceedings (2023)
2023
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Ruiz, N., Li, Y., Jampani, V., Pritch, Y., Rubinstein, M., Aberman, K.: Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2023)
2023
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2023
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Tancik, M., Weber, E., Ng, E., Li, R., Yi, B., Kerr, J., Wang, T., Kristoffersen, A., Austin, J., Salahi, K., Ahuja, A., McAllister, D., Kanazawa, A.: Nerfstudio: A modular framework for neural radiance field development. In: ACM SIGGRAPH 2023 Conference Proceedings. SIGGRAPH ’23 (2023)
2023
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Zhang, L., Rao, A., Agrawala, M.: Adding conditional control to text-to-image diffusion models (2023)
2023
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2023
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Vachha, C., Haque, A.: Instruct-gs2gs: Editing 3d gaussian splats with instructions (2024), https://instruct-gs2gs.github.io/
2024
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